Overview

Dataset statistics

Number of variables10
Number of observations1630
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory127.5 KiB
Average record size in memory80.1 B

Variable types

Numeric10

Alerts

2022-09-01 00:00:00 is highly overall correlated with 2022-09-02 00:00:00 and 6 other fieldsHigh correlation
2022-09-02 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-03 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-04 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-05 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-06 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-07 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
2022-09-08 00:00:00 is highly overall correlated with 2022-09-01 00:00:00 and 6 other fieldsHigh correlation
TID has unique valuesUnique
2022-09-01 00:00:00 has 82 (5.0%) zerosZeros
2022-09-02 00:00:00 has 90 (5.5%) zerosZeros
2022-09-03 00:00:00 has 119 (7.3%) zerosZeros
2022-09-04 00:00:00 has 95 (5.8%) zerosZeros
2022-09-05 00:00:00 has 95 (5.8%) zerosZeros
2022-09-06 00:00:00 has 149 (9.1%) zerosZeros
2022-09-07 00:00:00 has 112 (6.9%) zerosZeros
2022-09-08 00:00:00 has 80 (4.9%) zerosZeros

Reproduction

Analysis started2023-05-20 19:56:33.906616
Analysis finished2023-05-20 19:56:44.015746
Duration10.11 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

TID
Real number (ℝ)

Distinct1630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean642270.74
Minimum406136
Maximum699664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:44.080256image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum406136
5-th percentile606153.9
Q1619686.75
median635770
Q3668642
95-th percentile698657.1
Maximum699664
Range293528
Interquartile range (IQR)48955.25

Descriptive statistics

Standard deviation37592.92
Coefficient of variation (CV)0.058531267
Kurtosis13.064575
Mean642270.74
Median Absolute Deviation (MAD)25366.5
Skewness-2.1107172
Sum1.0469013 × 109
Variance1.4132277 × 109
MonotonicityStrictly increasing
2023-05-20T22:56:44.189198image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
406136 1
 
0.1%
649943 1
 
0.1%
652824 1
 
0.1%
652820 1
 
0.1%
652813 1
 
0.1%
649987 1
 
0.1%
649984 1
 
0.1%
649981 1
 
0.1%
649977 1
 
0.1%
649973 1
 
0.1%
Other values (1620) 1620
99.4%
ValueCountFrequency (%)
406136 1
0.1%
406139 1
0.1%
406145 1
0.1%
406148 1
0.1%
406180 1
0.1%
406190 1
0.1%
406196 1
0.1%
406504 1
0.1%
406509 1
0.1%
406536 1
0.1%
ValueCountFrequency (%)
699664 1
0.1%
699641 1
0.1%
699629 1
0.1%
699579 1
0.1%
699578 1
0.1%
699577 1
0.1%
699572 1
0.1%
699560 1
0.1%
699540 1
0.1%
699451 1
0.1%
Distinct640
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean319542.94
Minimum0
Maximum6019000
Zeros12
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:44.308284image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile48450
Q1149250
median288000
Q3446750
95-th percentile669550
Maximum6019000
Range6019000
Interquartile range (IQR)297500

Descriptive statistics

Standard deviation258533.08
Coefficient of variation (CV)0.80907146
Kurtosis153.31332
Mean319542.94
Median Absolute Deviation (MAD)146000
Skewness7.885701
Sum5.20855 × 108
Variance6.6839352 × 1010
MonotonicityNot monotonic
2023-05-20T22:56:44.489784image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
0.7%
160000 9
 
0.6%
100000 9
 
0.6%
155000 9
 
0.6%
175000 8
 
0.5%
137000 8
 
0.5%
45000 8
 
0.5%
390000 7
 
0.4%
145000 7
 
0.4%
398000 7
 
0.4%
Other values (630) 1546
94.8%
ValueCountFrequency (%)
0 12
0.7%
8000 1
 
0.1%
9000 1
 
0.1%
10000 1
 
0.1%
11000 1
 
0.1%
13000 1
 
0.1%
14000 2
 
0.1%
16000 2
 
0.1%
17000 1
 
0.1%
18000 1
 
0.1%
ValueCountFrequency (%)
6019000 1
0.1%
2999000 1
0.1%
2347000 1
0.1%
1517000 1
0.1%
1185000 1
0.1%
1132000 1
0.1%
1098000 1
0.1%
1053000 1
0.1%
1042000 1
0.1%
1038000 1
0.1%

2022-09-01 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct188
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59214.724
Minimum0
Maximum729000
Zeros82
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:44.602654image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile450
Q133000
median50500
Q373000
95-th percentile139000
Maximum729000
Range729000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation48710.183
Coefficient of variation (CV)0.82260255
Kurtosis33.922335
Mean59214.724
Median Absolute Deviation (MAD)19500
Skewness3.9167166
Sum96520000
Variance2.3726819 × 109
MonotonicityNot monotonic
2023-05-20T22:56:44.714607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
 
5.0%
40000 41
 
2.5%
45000 40
 
2.5%
55000 32
 
2.0%
50000 30
 
1.8%
49000 30
 
1.8%
43000 30
 
1.8%
35000 27
 
1.7%
58000 27
 
1.7%
44000 27
 
1.7%
Other values (178) 1264
77.5%
ValueCountFrequency (%)
0 82
5.0%
1000 1
 
0.1%
2000 1
 
0.1%
5000 10
 
0.6%
6000 5
 
0.3%
7000 6
 
0.4%
8000 12
 
0.7%
9000 7
 
0.4%
10000 21
 
1.3%
11000 5
 
0.3%
ValueCountFrequency (%)
729000 1
0.1%
510000 1
0.1%
450000 1
0.1%
395000 1
0.1%
389000 1
0.1%
382000 1
0.1%
328000 1
0.1%
286000 1
0.1%
276000 1
0.1%
261000 2
0.1%

2022-09-02 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct193
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59465.644
Minimum0
Maximum684000
Zeros90
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:44.831891image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133000
median52000
Q375000
95-th percentile135550
Maximum684000
Range684000
Interquartile range (IQR)42000

Descriptive statistics

Standard deviation48139.617
Coefficient of variation (CV)0.80953662
Kurtosis30.167723
Mean59465.644
Median Absolute Deviation (MAD)21000
Skewness3.5686899
Sum96929000
Variance2.3174227 × 109
MonotonicityNot monotonic
2023-05-20T22:56:44.941454image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 90
 
5.5%
35000 37
 
2.3%
50000 33
 
2.0%
25000 32
 
2.0%
47000 32
 
2.0%
40000 31
 
1.9%
45000 27
 
1.7%
57000 27
 
1.7%
70000 27
 
1.7%
60000 26
 
1.6%
Other values (183) 1268
77.8%
ValueCountFrequency (%)
0 90
5.5%
2000 3
 
0.2%
3000 5
 
0.3%
5000 14
 
0.9%
6000 7
 
0.4%
7000 8
 
0.5%
8000 13
 
0.8%
9000 1
 
0.1%
10000 13
 
0.8%
11000 5
 
0.3%
ValueCountFrequency (%)
684000 1
0.1%
589000 1
0.1%
355000 1
0.1%
349000 1
0.1%
324000 1
0.1%
317000 1
0.1%
289000 1
0.1%
286000 1
0.1%
284000 1
0.1%
261000 1
0.1%

2022-09-03 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct195
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59044.172
Minimum0
Maximum1234000
Zeros119
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:45.058448image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131000
median52000
Q374000
95-th percentile139550
Maximum1234000
Range1234000
Interquartile range (IQR)43000

Descriptive statistics

Standard deviation53914.415
Coefficient of variation (CV)0.91312002
Kurtosis144.46969
Mean59044.172
Median Absolute Deviation (MAD)21500
Skewness7.8075904
Sum96242000
Variance2.9067642 × 109
MonotonicityNot monotonic
2023-05-20T22:56:45.178338image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
 
7.3%
40000 37
 
2.3%
55000 37
 
2.3%
50000 34
 
2.1%
45000 33
 
2.0%
20000 32
 
2.0%
53000 29
 
1.8%
25000 28
 
1.7%
58000 27
 
1.7%
52000 25
 
1.5%
Other values (185) 1229
75.4%
ValueCountFrequency (%)
0 119
7.3%
2000 2
 
0.1%
3000 2
 
0.1%
4000 1
 
0.1%
5000 2
 
0.1%
6000 3
 
0.2%
7000 4
 
0.2%
8000 5
 
0.3%
9000 6
 
0.4%
10000 12
 
0.7%
ValueCountFrequency (%)
1234000 1
0.1%
518000 1
0.1%
479000 1
0.1%
328000 1
0.1%
304000 1
0.1%
285000 1
0.1%
263000 1
0.1%
259000 2
0.1%
248000 1
0.1%
246000 2
0.1%

2022-09-04 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct182
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55165.644
Minimum0
Maximum713000
Zeros95
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:45.294118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131000
median48500
Q369000
95-th percentile125100
Maximum713000
Range713000
Interquartile range (IQR)38000

Descriptive statistics

Standard deviation43576.998
Coefficient of variation (CV)0.78993001
Kurtosis43.133336
Mean55165.644
Median Absolute Deviation (MAD)18500
Skewness4.1152211
Sum89920000
Variance1.8989547 × 109
MonotonicityNot monotonic
2023-05-20T22:56:45.404746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 95
 
5.8%
45000 41
 
2.5%
40000 38
 
2.3%
35000 34
 
2.1%
65000 32
 
2.0%
55000 31
 
1.9%
38000 31
 
1.9%
60000 30
 
1.8%
50000 30
 
1.8%
47000 29
 
1.8%
Other values (172) 1239
76.0%
ValueCountFrequency (%)
0 95
5.8%
1000 1
 
0.1%
2000 1
 
0.1%
4000 1
 
0.1%
5000 7
 
0.4%
6000 2
 
0.1%
7000 4
 
0.2%
8000 9
 
0.6%
9000 8
 
0.5%
10000 23
 
1.4%
ValueCountFrequency (%)
713000 1
0.1%
522000 1
0.1%
352000 1
0.1%
333000 1
0.1%
295000 1
0.1%
238000 1
0.1%
231000 1
0.1%
225000 1
0.1%
219000 1
0.1%
217000 1
0.1%

2022-09-05 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct190
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56202.454
Minimum0
Maximum641000
Zeros95
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:45.521138image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130000
median49000
Q371000
95-th percentile132000
Maximum641000
Range641000
Interquartile range (IQR)41000

Descriptive statistics

Standard deviation46202.341
Coefficient of variation (CV)0.82206982
Kurtosis28.801362
Mean56202.454
Median Absolute Deviation (MAD)21000
Skewness3.5500805
Sum91610000
Variance2.1346563 × 109
MonotonicityNot monotonic
2023-05-20T22:56:45.630000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 95
 
5.8%
45000 42
 
2.6%
50000 38
 
2.3%
55000 35
 
2.1%
35000 33
 
2.0%
25000 31
 
1.9%
15000 30
 
1.8%
60000 29
 
1.8%
53000 26
 
1.6%
47000 26
 
1.6%
Other values (180) 1245
76.4%
ValueCountFrequency (%)
0 95
5.8%
1000 1
 
0.1%
3000 3
 
0.2%
5000 13
 
0.8%
6000 4
 
0.2%
7000 12
 
0.7%
8000 7
 
0.4%
9000 8
 
0.5%
10000 18
 
1.1%
11000 7
 
0.4%
ValueCountFrequency (%)
641000 1
0.1%
512000 1
0.1%
492000 1
0.1%
327000 1
0.1%
281000 1
0.1%
280000 1
0.1%
276000 2
0.1%
271000 1
0.1%
263000 1
0.1%
250000 1
0.1%

2022-09-06 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct183
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54279.141
Minimum0
Maximum841000
Zeros149
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:45.750667image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q128000
median48000
Q370000
95-th percentile133550
Maximum841000
Range841000
Interquartile range (IQR)42000

Descriptive statistics

Standard deviation47482.503
Coefficient of variation (CV)0.87478361
Kurtosis52.07886
Mean54279.141
Median Absolute Deviation (MAD)21000
Skewness4.3871173
Sum88475000
Variance2.2545881 × 109
MonotonicityNot monotonic
2023-05-20T22:56:45.856174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 149
 
9.1%
50000 42
 
2.6%
40000 40
 
2.5%
45000 36
 
2.2%
55000 36
 
2.2%
60000 31
 
1.9%
30000 28
 
1.7%
43000 26
 
1.6%
48000 24
 
1.5%
38000 24
 
1.5%
Other values (173) 1194
73.3%
ValueCountFrequency (%)
0 149
9.1%
2000 2
 
0.1%
3000 4
 
0.2%
4000 1
 
0.1%
5000 7
 
0.4%
6000 7
 
0.4%
7000 15
 
0.9%
8000 15
 
0.9%
9000 9
 
0.6%
10000 21
 
1.3%
ValueCountFrequency (%)
841000 1
0.1%
450000 1
0.1%
335000 2
0.1%
307000 1
0.1%
289000 1
0.1%
263000 2
0.1%
262000 1
0.1%
256000 1
0.1%
233000 1
0.1%
231000 1
0.1%

2022-09-07 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct194
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57016.564
Minimum0
Maximum962000
Zeros112
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:45.967471image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130000
median50000
Q373000
95-th percentile140000
Maximum962000
Range962000
Interquartile range (IQR)43000

Descriptive statistics

Standard deviation48522.761
Coefficient of variation (CV)0.85102919
Kurtosis77.776145
Mean57016.564
Median Absolute Deviation (MAD)21000
Skewness5.2030176
Sum92937000
Variance2.3544583 × 109
MonotonicityNot monotonic
2023-05-20T22:56:46.083264image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 112
 
6.9%
55000 44
 
2.7%
50000 37
 
2.3%
40000 37
 
2.3%
35000 33
 
2.0%
45000 30
 
1.8%
15000 27
 
1.7%
60000 25
 
1.5%
30000 25
 
1.5%
25000 24
 
1.5%
Other values (184) 1236
75.8%
ValueCountFrequency (%)
0 112
6.9%
2000 2
 
0.1%
3000 3
 
0.2%
4000 1
 
0.1%
5000 16
 
1.0%
6000 3
 
0.2%
7000 12
 
0.7%
8000 18
 
1.1%
9000 5
 
0.3%
10000 23
 
1.4%
ValueCountFrequency (%)
962000 1
0.1%
456000 1
0.1%
293000 1
0.1%
283000 1
0.1%
265000 1
0.1%
258000 1
0.1%
237000 1
0.1%
230000 1
0.1%
225000 2
0.1%
223000 1
0.1%

2022-09-08 00:00:00
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct190
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58061.35
Minimum0
Maximum1181000
Zeros80
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-05-20T22:56:46.275196image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3000
Q132000
median50000
Q372000
95-th percentile138000
Maximum1181000
Range1181000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation55491.453
Coefficient of variation (CV)0.95573825
Kurtosis131.88941
Mean58061.35
Median Absolute Deviation (MAD)20000
Skewness8.1426933
Sum94640000
Variance3.0793013 × 109
MonotonicityNot monotonic
2023-05-20T22:56:46.390664image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 80
 
4.9%
35000 39
 
2.4%
50000 38
 
2.3%
45000 35
 
2.1%
55000 30
 
1.8%
40000 29
 
1.8%
15000 28
 
1.7%
30000 27
 
1.7%
42000 26
 
1.6%
63000 26
 
1.6%
Other values (180) 1272
78.0%
ValueCountFrequency (%)
0 80
4.9%
2000 1
 
0.1%
3000 2
 
0.1%
4000 2
 
0.1%
5000 9
 
0.6%
6000 4
 
0.2%
7000 13
 
0.8%
8000 9
 
0.6%
9000 4
 
0.2%
10000 20
 
1.2%
ValueCountFrequency (%)
1181000 1
0.1%
817000 1
0.1%
592000 1
0.1%
495000 1
0.1%
356000 1
0.1%
318000 1
0.1%
276000 1
0.1%
247000 1
0.1%
244000 1
0.1%
227000 1
0.1%

Interactions

2023-05-20T22:56:42.797874image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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Correlations

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TIDостаток на 31.08.2022 (входящий)2022-09-01 00:00:002022-09-02 00:00:002022-09-03 00:00:002022-09-04 00:00:002022-09-05 00:00:002022-09-06 00:00:002022-09-07 00:00:002022-09-08 00:00:00
TID1.000-0.0880.0040.0000.0430.000-0.024-0.0130.0180.005
остаток на 31.08.2022 (входящий)-0.0881.0000.3160.3130.2950.2920.3040.2940.3070.314
2022-09-01 00:00:000.0040.3161.0000.7260.7540.7480.7900.6780.7440.755
2022-09-02 00:00:000.0000.3130.7261.0000.6910.7610.7550.7130.7220.736
2022-09-03 00:00:000.0430.2950.7540.6911.0000.7270.7300.6500.7570.754
2022-09-04 00:00:000.0000.2920.7480.7610.7271.0000.6960.6510.6980.739
2022-09-05 00:00:00-0.0240.3040.7900.7550.7300.6961.0000.6270.7400.753
2022-09-06 00:00:00-0.0130.2940.6780.7130.6500.6510.6271.0000.5530.673
2022-09-07 00:00:000.0180.3070.7440.7220.7570.6980.7400.5531.0000.693
2022-09-08 00:00:000.0050.3140.7550.7360.7540.7390.7530.6730.6931.000

Missing values

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A simple visualization of nullity by column.
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Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TIDостаток на 31.08.2022 (входящий)2022-09-01 00:00:002022-09-02 00:00:002022-09-03 00:00:002022-09-04 00:00:002022-09-05 00:00:002022-09-06 00:00:002022-09-07 00:00:002022-09-08 00:00:00
04061361600009000010500099000107000110000600007500089000
140613938700010300020600016800012400078000165000164000174000
2406145287000143000136000124000117000123000140000139000138000
340614835500050000730005300065000750001000005300052000
44061805970009600082000710007200086000550005500075000
5406190140000219000236000218000212000207000174000131000197000
640619631800011500012300012100012000096000122000127000112000
7406504819000382000317000479000333000232000335000225000318000
8406509892000128000126000170000113000120000136000109000169000
94065366510006300065000002010008000013300068000
TIDостаток на 31.08.2022 (входящий)2022-09-01 00:00:002022-09-02 00:00:002022-09-03 00:00:002022-09-04 00:00:002022-09-05 00:00:002022-09-06 00:00:002022-09-07 00:00:002022-09-08 00:00:00
16206994511410004700061000680007600051000620006000054000
1621699540160000800001020001400007800019600078000490000
16226995600110000570001550001920001270008200060000117000
162369957265000012400001520001610005300005000113000
1624699577375000025000002700015000028000
16256995784700000100000100006000025000
162669957923600049000680000013000500000132000
1627699629670006300063000630006400074000012100063000
162869964127800063000005100000770000
162969966433300000470000430000036000